The journal of nutrition, health & aging

, Volume 21, Issue 10, pp 1233–1239 | Cite as

Model construction for biological age based on a cross-sectional study of a healthy Chinese han population

  • W. Zhang
  • L. Jia
  • G. Cai
  • F. Shao
  • H. Lin
  • Z. Liu
  • F. Liu
  • D. Zhao
  • Z. Li
  • X. Bai
  • Z. Feng
  • XueFeng SunEmail author
  • Xiang-Mei ChenEmail author



Biological age (BA) has been proposed to evaluate the aging status in an objective way instead of chronological age (CA). The purpose of our study is to construct a more precise formula of BA in the cross-sectional study based on a largest-ever sample of our studies. This formula aims at better evaluation of body function and exploring the disciplines of aging in different genders and age stages.


A total of 1,373 healthy Chinese Han (age range, 19-93 years) were recruited from five cities in China, including 581 males and 792 females. Physical examination, blood routine, blood chemistry, and other lab tests were performed to obtain a total of 74 clinical variables. Then, the principal component analysis (PCA) was used to select variables and estimate BA. The BA formula was further validated in a population with some diseases (n=266), including cardiovascular diseases, type 2 diabetes, kidney diseases, pulmonary diseases, cancer and disorders in nervous system.


The BA formula was constructed as follows: BA = 0.358 (pulse pressure) + 0.258 (trail making test)–11.552 (mitral valve E/A peak) + 26.383 (minimum intima-media thickness) + 31.965 (Cystatin C) + 0.163 (CA)–3.902. In validation of the formula, BAs of patients were older than those of healthy persons. The BA accelerates faster in the middle-aged population than in the elderly population (>75 years old).


This BA formula can reflect health condition changes of aging better than CA in a Chinese Han population.


Biological age chronological age principal component analysis 


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Copyright information

© Serdi and Springer-Verlag France 2017

Authors and Affiliations

  • W. Zhang
    • 1
  • L. Jia
    • 2
  • G. Cai
    • 1
  • F. Shao
    • 3
  • H. Lin
    • 4
  • Z. Liu
    • 5
  • F. Liu
    • 6
  • D. Zhao
    • 1
  • Z. Li
    • 1
  • X. Bai
    • 7
  • Z. Feng
    • 1
  • XueFeng Sun
    • 1
    • 8
    Email author
  • Xiang-Mei Chen
    • 1
    • 8
    Email author
  1. 1.Department of NephrologyChinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney DiseasesBeijingChina
  2. 2.Department of NephrologySecond Hospital of Jilin UniversityChangchun, Jilin ProvinceChina
  3. 3.Department of NephrologyPeople’s Hospital of Henan ProvinceZhengzhou, Henan ProvinceChina
  4. 4.Department of NephrologyFirst Affiliated Hospital of Dalian Medical UniversityDalian, Liaoning ProvinceChina
  5. 5.Department of NephrologyFirst Affiliated Hospital of Zhengzhou UniversityZhengzhou, Henan ProvinceChina
  6. 6.Department of Nephrology, Second Xiangya HospitalCentral South UniversityChangsha, Hunan ProvinceChina
  7. 7.Department of Gerontology and GeriatricsShengJing Hospital of China Medical UniversityShenyang, Liaoning ProvinceChina
  8. 8.Department of NephrologyKidney Institute of Chinese PLA, Chinese PLA General Hospital, State Key Laboratory of Kidney DiseasesBeijingChina

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